mirror of
https://github.com/hanzoai/mugen.git
synced 2026-11-03 01:48:40 +00:00
35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
|
# All rights reserved.
|
|
#
|
|
# This source code is licensed under the license found in the
|
|
# LICENSE file in the root directory of this source tree.
|
|
|
|
"""
|
|
Grid search file, simply list all the exp you want in `explorer`.
|
|
Any new exp added there will be scheduled.
|
|
You can cancel and experiment by commenting its line.
|
|
|
|
This grid shows how to train a MusicGen EnCodec model at 32 kHz.
|
|
"""
|
|
|
|
from ._explorers import CompressionExplorer
|
|
from ...environment import AudioCraftEnvironment
|
|
|
|
|
|
@CompressionExplorer
|
|
def explorer(launcher):
|
|
partitions = AudioCraftEnvironment.get_slurm_partitions(['team', 'global'])
|
|
launcher.slurm_(gpus=8, partition=partitions)
|
|
# use configuration for MusicGen's EnCodec model trained on monophonic audio sampled at 32 kHz
|
|
# MusicGen's EnCodec is trained with a total stride of 640 leading to a frame rate of 50 hz
|
|
launcher.bind_(solver='compression/encodec_musicgen_32khz')
|
|
# replace this by the desired music dataset
|
|
launcher.bind_(dset='internal/music_400k_32khz')
|
|
# launch xp
|
|
launcher()
|
|
launcher({
|
|
'metrics.visqol.bin': '/data/home/jadecopet/local/usr/opt/visqol',
|
|
'label': 'visqol',
|
|
'evaluate.metrics.visqol': True
|
|
})
|